Chemistry Learning Research Articles

PENGARUH STRATEGI STRENGTHENING, ORIENTATION, INVESTIGATION, EVALUATION (SOIE) TERHADAP LITERASI KIMIA PESERTA DIDIK

This research aims to determine the influence of the Strengthening, Orientation, Investigation, Evaluation (SOIE) strategy on students' chemical literacy at SMA Negeri 1 Lhokseumawe. This research was carried out in the odd semester of the 2023/2024 academic year in classes XI-1 and XI-4. The type of research used is quasi-experiment (quasi-experiment) with a quantitative approach. The sampling technique in this research is purposive sampling. The sample in this study was class X1-I as an experimental class with a total of 36 students and class XI-4 as a control class with a total of 33 students. The research sample has been tested for normality and homogeneity requirements. The data collection technique uses essay questions. The test was carried out at the end (posttest) in the experimental class and control class. Hypothesis testing using the Mann-Whitney test, obtained a sig value. (2-tailed) 0.001 < 0.05 on posttest results. Based on the test results, it can be concluded that there is an influence of the SOIE strategy on students' chemical literacy at SMA Negeri 1 Lhokseumawe and the SOIE strategy can contribute positively to students' chemical literacy on reaction rate material according to the sig value. (2-tailed) 0.000 < 0.05 and strengthens understanding of concepts and encourages active involvement of students in the chemistry learning process.

AGILE platform: a deep learning powered approach to accelerate LNP development for mRNA delivery

Ionizable lipid nanoparticles (LNPs) are seeing widespread use in mRNA delivery, notably in SARS-CoV-2 mRNA vaccines. However, the expansion of mRNA therapies beyond COVID-19 is impeded by the absence of LNPs tailored for diverse cell types. In this study, we present the AI-Guided Ionizable Lipid Engineering (AGILE) platform, a synergistic combination of deep learning and combinatorial chemistry. AGILE streamlines ionizable lipid development with efficient library design, in silico lipid screening via deep neural networks, and adaptability to diverse cell lines. Using AGILE, we rapidly design, synthesize, and evaluate ionizable lipids for mRNA delivery, selecting from a vast library. Intriguingly, AGILE reveals cell-specific preferences for ionizable lipids, indicating tailoring for optimal delivery to varying cell types. These highlight AGILE’s potential in expediting the development of customized LNPs, addressing the complex needs of mRNA delivery in clinical practice, thereby broadening the scope and efficacy of mRNA therapies.

The Effectiveness of the Ethnochemistry-based Problem Based Learning Model on Students' Problem-Solving Ability in Chemistry Learning: A Meta-analysis Study in 2021-2024

This research is based on many ethnoscience-based problem-based learning studies on students' problem-solving skills. However, many different studies are related to drawing conclusions regarding the application of ethnochemistry-based project-based learning to students' problem-solving skills. This study aims to analyze the influence of ethnochemistry-based problem-based learning model on students' problem-solving ability in chemistry learning. Compared to conventional models. This research is a type of meta-analysis research. Data collection techniques through google scholar database searching; ERIC; ScienceDirect; Wiley; and IEEE. The research data was analyzed to calculate the effect size value of 17 primary studies that met the inclusion criteria. Data analysis with the help of JSAP 0.16.3 software. The results of this study concluded that the ethnochemistry-based problem-based learning model had a significant influence on students' problem-solving ability with an mean effect size ( d = 0.997; p < 0.001) including the high effect size category. These findings conclude that the ethnochemistry-based problem-based learning model is effective in improving students' problem-solving skills compared to conventional learning models. The results of the meta-analysis provide more accurate information so that it can improve the quality of chemistry learning for students at school.

Development of E-Module Acid-Base Based on Problem Based Learning Oriented Chemo-Entrepreneurship to Improve Student’s Critical Thinking Skills

Acid-base is one of the important materials in chemistry learning. Based on preliminary analysis, it is known that students have not properly understood the concept of acid-base. This study aims to develop an acid-base e-module, analyze its validity, practicality, and effectiveness on critical thinking skills. This research method is development research with the Plomp development model. The e-module was validated by 5 valitadors. The practicality test was conducted on 28 students and 3 teachers. The effectiveness of the e-module is seen from the increase in critical thinking test score from 57 students. Validity and practicality were analyzed using Aiken's V, while effectiveness was analyzed with N-Gain. The results showed that the developed e-module had a validity value of 0.89 with a valid category; a practicality value of 0.87 by students and 0.97 by teachers with a practical category. The effectiveness results show that the e-module has an effect on students' critical thinking skills, as evidenced by the N-Gain score of the experimental class of 0,7 with a fairly effective category while the N-Gain score of the control class is 0,4 with a less effective category. Thus, the developed e-module is declared valid, practical, and effective.

Description of Students' Multirepresentation Ability on Hydrocarbon Material at SMA Negeri 1 Sungai Kunyit

Material in chemistry learning will be easier to understand if students are able to represent it at three levels of representation, namely macroscopic, sub-microscopic and symbolic. This research aims to describe students' abilities in using various representations in class XI MIPA 1 hydrocarbon material at SMA Negeri 1 Sungai Kunyit. Students' thinking processes require various representations and various ways or steps to solve problems. The type of research used is quantitative descriptive research. The research instruments used included 9 two tier multiple choice objective test questions and an interview guide. This research involved 20 students of class XI MIPA 1 SMA Negeri 1 Sungai Kunyit. The research results show that overall, the average multi-representation ability of students is 29% in the poor category. At the macroscopic representation level, the average percentage obtained is 20% which can be classified as very poor. At the sub-microscopic level of representation, the average is 35% which is included in the poor category. Finally, at the level of symbolic representation the average percentage is 31% which is also included in the poor category.

Media Pembelajaran Kimia Berbasis AR

The integration of augmented reality (AR) technology in education is advancing, as seen in a project at Atisa Dipamkara School. This project developed a chemistry learning application using Unity, Android XR Plugin, and ARCore to address laboratory limitations. The app uses interactive 3D visualizations to help students grasp complex chemistry concepts. Blackbox testing showed that all main modules work well, except for a bug in the compound reset module. The app effectively improves students' understanding, interest, and motivation in chemistry, making abstract concepts more tangible. This application is both a learning aid and an educational innovation, promoting a more interactive and enjoyable learning experience.

Augmented reality for chemistry education to promote the use of chemical terminology in teacher training.

Chemistry as a whole is divided into three levels. The macroscopic level describes real, observable phenomena of the material world. The submicroscopic level focuses on particles. The representative level includes pictorial and symbolic representations to visualize substance in its nature. Students often have problems separating these levels and conceptually transfer each of the three levels to the other. Therefore, teachers need to use chemical terminology correctly when teaching the substance-particle concept. Augmented Reality (AR) connects real and virtual world. The observer physically moves in a real environment that integrates virtual elements. The AR technology has great potential for learning in the subject chemistry, especially when it comes to making the "invisible" visible and illustrating scientific phenomena at particle level. The simultaneous presentation should avoid split-attention and offers new possibilities to interactively deal with (M)ER. The question arises whether AR has a positive effect on the use of technical language and the associated understanding of the concept of dealing with (M)ER at the substance and particle levels. With an AR app on the tablet and the AR glasses, the chemical processes of a real experiment are represented by AR visualizations. Therefore, the AR app was piloted. This study captured the chemistry handling with (M)ER of chemistry teachers (N = 30) using a pre-post survey. The participating preservice teachers are described below. Each test includes five tasks elaborated by thinking aloud. The thinking-aloud protocols to acquire the use of the chemical terminology are evaluated in MAXQDA.

Many-Body Function Corrected Neural Network with Atomic Attention (MBNN-att) for Molecular Property Prediction.

Recent years have seen a surge of machine learning (ML) in chemistry for predicting chemical properties, but a low-cost, general-purpose, and high-performance model, desirable to be accessible on central processing unit (CPU) devices, remains not available. For this purpose, here we introduce an atomic attention mechanism into many-body function corrected neural network (MBNN), namely, MBNN-att ML model, to predict both the extensive and intensive properties of molecules and materials. The MBNN-att uses explicit function descriptors as the inputs for the atom-based feed-forward neural network (NN). The output of the NN is designed to be a vector to implement the multihead self-attention mechanism. This vector is split into two parts: the atomic attention weight part and the many-body-function part. The final property is obtained by summing the products of each atomic attention weight and the corresponding many-body function. We show that MBNN-att performs well on all QM9 properties, i.e., errors on all properties, below chemical accuracy, and, in particular, achieves the top performance for the energy-related extensive properties. By systematically comparing with other explicit-function-type descriptor ML models and the graph representation ML models, we demonstrate that the many-body-function framework and atomic attention mechanism are key ingredients for the high performance and the good transferability of MBNN-att in molecular property prediction.

Effectiveness of Inquiry-Based Chemistry Learning on Students’ Attitudes and Knowledge of Climate Change Mitigation Behaviors

Effectiveness of Inquiry-Based Chemistry Learning on Students’ Attitudes and Knowledge of Climate Change Mitigation Behaviors

Building Bridges: How Integrated STEM with Problem-Based Learning Can Enhance Student Critical Thinking and Learning Outcomes in Chemistry

Low critical thinking skills and student learning outcomes are still widely found, especially in chemistry learning. This study aims to analyze the application of STEM integrated problem-based learning (PBL) on chemistry materials, and to analyze STEM-based learning integrated with PBL to improve students' critical thinking skills and learning outcomes on chemistry materials. The method used in this research is a systematic literature review based on articles traced through Google Schoolar, Garuda, and ERIC databases. The data obtained was then analysed descriptively. The results showed that: (1) From a number of STEM-PBL implementations that have been carried out in various fields, the implementation of STEM-PBL in chemistry learning obtained a percentage of 32%; (2) STEM-PBL implementation can improve students' critical thinking skills and learning outcomes ranging from moderate to high categories. STEM-PBL learning is effectively used to improve critical thinking skills and learning outcomes, so it can be used as an alternative in chemistry learning.

Learning Assistants and Instructors Provide Social Support That Influences Student Engagement Differently in Undergraduate Active Learning Chemistry Courses

Learning Assistants and Instructors Provide Social Support That Influences Student Engagement Differently in Undergraduate Active Learning Chemistry Courses

PHYSICS EDUCATION TECHNOLOGY (PhET) SIMULATION AS AID IN INSTRUCTION IN LEARNING CHEMISTRY: AN EXPERIMENTAL APPROACH

The objective of this study was to evaluate the influence of the inclusion of Physics Educational Technology (PhET) Simulations as an aid in instruction in learning chemistry to the Grade 10 learners at Sinobong National High School, a public secondary school in Agusan del Sur. A quantitative study involving pretest-posttest quasi-experimental design was employed to validate the proposed hypotheses. There were 80 participants randomly assigned to the control and experimental groups. The instruments used for data collection were a validated 50-item pre-test/post-test adapted from the Grade 10 Teachers’ Guide unified test in the K to 12 science curricula used by the secondary schools. In addition, the mean score and t-test statistical analysis were used to analyze the given data. The results showed a substantial difference between the experimental and control groups' post-test scores. The data support the claim that PhET Simulation significantly influences students' academic attainment compared to a traditional teaching strategy. The researcher suggested that teachers should involve Phet Simulation in their classroom instructions and learning process, and administrators should provide more professional development, workshops, and training to abreast the technological advancement of Phet in chemistry learning. KEYWORDS: MAED, Teaching Science, PhET Simulation, traditional teaching strategy, academic attainment

RADEC Learning Model as an Alternative in Chemistry Learning: A Literature Study

RADEC Learning Model as an Alternative in Chemistry Learning: A Literature Study

PENERAPAN MODEL PEMBELAJARAN PROBLEM BASED LEARNING (PBL) PADA MATERI PERUBAHAN FISIKA DAN PERUBAHAN KIMIA SMK

Learning is required to provide opportunities for students to be involved in the learning process, including chemistry learning. Learning chemistry is still a scourge for most children, or is considered a difficult subject. Based on observations and interviews, the results showed that students were less actively involved in learning activities. This is because teachers have not optimized the use of methods and innovative learning models. This research focuses more on the application of the PBL learning model. The hope is that students will be motivated to study chemistry, especially the topic of physical and chemical changes. This research is a qualitative descriptive study. Data processing techniques are carried out by describing the data collected and analyzing the implementation of learning, in order to find best practices that can be disseminated. The impact of applying the problem based learning model on material on physical changes and chemical changes is very affective because it can make students active in participating in learning activities and learning outcomes also increase. In order to make learning innovation work well in the future, you must: Carry out careful planning in the learning process which can be done through coordination with teachers and education staff. Careful planning ensures that innovation will not disrupt the flow of in-depth learning of the material. On the other hand, innovation can support a better level of understanding of the material.

The defect chemistry and machine learning study 5d transition metal doped on graphitic carbon nitride for bifunctional oxygen electrocatalyst with low overpotential

Searching for highly efficient bifunctional oxygen evolution reaction/oxygen reduction reaction (OER/ORR) electrocatalysts for sustainable and renewable clean energy is vital. However, these electrocatalyst designs remain cost-prohibitive for both experimental and computational studies. This paper systematically investigates 5d transition metal (5d TM) doped into graphitic carbon nitride (g-C3N3) as potential bifunctional OER/ORR electrocatalysts by considering the defect charge states through the defect chemistry study. Our formation energies results show that 33 kinds of 5d TM doped g-C3N3 have better stabilities in the different charge states. Among them, IrN×@C54N53 (Ir occupation N), IrN•@C54N53, PtN×@C54N53 (Pt occupation N), and Iri•@C54N54 (Ir interstitial sites) exhibit lower overpotentials. They are great candidates for bifunctional OER/ORR electrocatalysts. This is because adjusting the charge states of 5d-TM@g-C3N3 can tune the interaction strength of the oxygenated intermediates. Furthermore, machine learning shows that the charge transfer of TM atoms (Qe) and total magnetic moment (μB0) are the two most essential descriptors for OER and ORR overpotential, respectively. The charged defect adjusting of the bifunctional OER/ORR activity would develop the potential electrocatalysts for energy conversion applications.

Development of Website based Multiple Representation on Buffer Solution Topic in Chemistry Learning

Buffer solution is one of chemistry difficult topics. It contains theory, calculation, and experimentation, so it requires good analysis and understanding of concepts. The results of interviews with students in Bintan Regency showed that the sub material of determining buffer solution components and analyzing the working principles of buffer solutions was the most difficult part because it was abstract. Multiple representations on the website media will visualize abstract things from the topic of buffer solution so as to increase the understanding of concepts from students. The research aims to produce multiple representation website on buffer solution topics and to determine its feasibility, practicality, and readability. The research method used is research and development (RD) following the 4D development model by Thiagrajan (define, design, develop, and disseminate). The sample research used 21 students and five chemistry teachers in Bintan Regency to collect user responses related to practicality and readability. The data analysis calculates the average score of the validation and response values and classifies them into the available categories. The results of the validation show that the average score of material experts is 63.5 (learning, materials, multiple representations, and evaluation aspects), while the average score of media experts is 71.5 (graphic design, software engineering, and media selection criteria aspects), which are classified as very good. The results of practicality and readability responses are 119 (learning, materials, multiple representations, evaluation, graphic design, software engineering, and media selection criteria) and 70.5 (learning, graphic design, and software engineering), which are very good categories

ANALYSIS OF STUDENT LEARNING INDEPENDENCE IN THE IMPLEMENTATION OF UKBM (INDEPENDENT LEARNING ACTIVITIES UNITS) IN LEARNING CHEMISTRY HYDROCARBON MATERIAL

Study This aim For know application of UKBM Chemistry and independence Study student in implementation of UKBM. Study This carried out at MAN 2 Padang Lawas. Study This is study qualitative with method approach quantitative . Subject in study This is class XI MIA 1, XI MIA 2 and XI MIA 3 where third class the in learning chemistry Already using UKBM Chemistry. Data collection techniques were carried out with interviews , observations , and questionnaires . Research result obtained : 1) Based on results interview with Vice Principal Curriculum and eyes lesson chemistry concluded implementation of UKBM Chemistry is underway with well and have been in accordance with instruction technical from government . The implementation of UKBM Chemistry is ongoing with Good seen from results observation by 70% and results evaluation checklist sheet by 85%. 2) Based on results interview with an eye teacher lesson chemistry , students can Study independent in accordance with UKBM flow that has been arranged . Based on the results of the questionnaire, the level of student learning independence in chemistry learning is in the good category at 78.66%. From this data it can be concluded that student learning independence in implementing UKBM in Chemistry Learning for class XI MIA MAN 2 Padang Lawas can be said to be good.

Uncertainty quantification by direct propagation of shallow ensembles

Statistical learning algorithms provide a generally-applicable framework to sidestep time-consuming experiments, or accurate physics-based modeling, but they introduce a further source of error on top of the intrinsic limitations of the experimental or theoretical setup. Uncertainty estimation is essential to quantify this error, and to make application of data-centric approaches more trustworthy. To ensure that uncertainty quantification is used widely, one should aim for algorithms that are accurate, but also easy to implement and apply. In particular, including uncertainty quantification on top of an existing architecture should be straightforward, and add minimal computational overhead. Furthermore, it should be easy to manipulate or combine multiple machine-learning predictions, propagating uncertainty over further modeling steps. We compare several well-established uncertainty quantification frameworks against these requirements, and propose a practical approach, which we dub direct propagation of shallow ensembles, that provides a good compromise between ease of use and accuracy. We present benchmarks for generic datasets, and an in-depth study of applications to the field of atomistic machine learning for chemistry and materials. These examples underscore the importance of using a formulation that allows propagating errors without making strong assumptions on the correlations between different predictions of the model.

Effectiveness of The Interactive Media-Assisted Electrolysis Module on Students' Conceptual Understanding

Teaching materials are an important aspect of supporting the learning process. Modules can be used as an alternative that makes students play an active role in understanding chemistry learning concepts. Therefore, this research aims to develop a module assisted by interactive media and determine its feasibility in understanding students' concepts. Analyisis, design, development, implementation, dan evaluation (ADDIE) development model was utilized in the research, which was carried out utilizing a research and development (RD). The interactive media-assisted module was implemented employing a nonequivalent posttest-only control group design. Class XII students at MAS Ulumul Qur'an Langsa made up the study's population. The sample for this research is class data collection through validation sheets, test questions, and questionnaires. The results of the validity test show that the module developed is included in the valid and reliable category with an average content validaty index (CVI) assessment score of 1.00 and an inter-rater agreement (IRA) of 98.25%. The data analysis outcomes that come from comprehending the concept using the t test obtained a sig value. (2-tailed) 0.0000.05 indicates that there is a significant difference in conceptual understanding between students who use modules assisted by interactive media and those who use printed books. The results of this research show that this interactive media-assisted module is very suitable for use, so it can be concluded that using this module can increase students' understanding of concepts

Investigating the influence of temperature on salt solubility in water: a STEM approach with pre-university chemistry students

Abstract In a society heavily influenced by technological advancements, developing scientific and technological literacy among young people is essential. Along these lines, this research describes a STEM activity developed to promote the teaching of chemistry content related to the solubility of potassium nitrate in water. It also facilitated the mastery of technological skills such as programming Arduino microcontrollers and using Microsoft Excel as tools for automatic data acquisition and analysis. Eighty pre-university Chemistry students participated in this research. This pedagogical approach was divided into three main stages: (1) preliminary research on components used in the experimental apparatus; (2) introduction to the assembly of electrical circuits and Arduino programming; (3) experimental investigation of the dependence of potassium nitrate solubility on temperature. The activity allowed the students to successfully achieve the proposed chemistry learning objectives while mobilizing other scientific and technological knowledge and skills. Despite the students’ limited prior knowledge of programming and electronics, as well as their limited proficiency in data analysis software, the integration of programming in the Chemistry class proved to be a differentiating factor with a highly positive impact, particularly in terms of motivation and interest among most students.